We performed a comparison between Elastic Search and OpenText IDOL based on real PeerSpot user reviews.
Find out in this report how the two Indexing and Search solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The initial setup is very easy for small environments."
"The solution offers good stability."
"The observability is the best available because it provides granular insights that identify reasons for defects."
"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."
"Helps us to store the data in key value pairs and, based on that, we can produce visualisations in Kibana."
"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."
"The product is scalable with good performance."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"IDOL has several important visual analytics, like face recognition and object detection and recognition."
"The one area that can use improvement is the automapping of fields."
"Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."
"The documentation regarding customization could be better."
"They're making changes in their architecture too frequently."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"There are challenges with performance management and scalability."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"There is room for improvement in some very important capabilities in visual analytics. They have been focusing on improving the face recognition algorithm. The accuracy of object detection could be improved as well and I know they are working on that at the moment."
Elastic Search is ranked 1st in Indexing and Search with 59 reviews while OpenText IDOL is ranked 3rd in Indexing and Search with 5 reviews. Elastic Search is rated 8.2, while OpenText IDOL is rated 8.4. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of OpenText IDOL writes "Scales linearly and vertically; primarily used in AI". Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Weaviate, whereas OpenText IDOL is most compared with Lucene. See our Elastic Search vs. OpenText IDOL report.
See our list of best Indexing and Search vendors.
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